Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations50000
Missing cells12476
Missing cells (%)1.6%
Total size in memory6.5 MiB
Average record size in memory136.0 B

Variable types

Numeric6
Text10

Alerts

post_code has 3836 (7.7%) missing valuesMissing
post_code_prefix has 3836 (7.7%) missing valuesMissing
country has 4609 (9.2%) missing valuesMissing
performance_reserved has 49760 (99.5%) zerosZeros

Reproduction

Analysis started2025-11-02 18:24:40.723325
Analysis finished2025-11-02 18:24:42.953128
Duration2.23 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Distinct40754
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1048820.559
Minimum6
Maximum1544309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:43.042495image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile105853.95
Q1691810
median1276043.5
Q31438385
95-th percentile1517556.2
Maximum1544309
Range1544303
Interquartile range (IQR)746575

Descriptive statistics

Standard deviation474204.6534
Coefficient of variation (CV)0.4521313482
Kurtosis-0.7110024814
Mean1048820.559
Median Absolute Deviation (MAD)217922.5
Skewness-0.8197643988
Sum5.244102796 × 1010
Variance2.248700533 × 1011
MonotonicityNot monotonic
2025-11-02T18:24:43.178518image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
614
 
< 0.1%
127090112
 
< 0.1%
59717610
 
< 0.1%
142588710
 
< 0.1%
14199399
 
< 0.1%
16439
 
< 0.1%
994109
 
< 0.1%
635069
 
< 0.1%
9078938
 
< 0.1%
12731088
 
< 0.1%
Other values (40744)49902
99.8%
ValueCountFrequency (%)
614
< 0.1%
202
 
< 0.1%
271
 
< 0.1%
281
 
< 0.1%
363
 
< 0.1%
ValueCountFrequency (%)
15443091
< 0.1%
15442891
< 0.1%
15442831
< 0.1%
15442091
< 0.1%
15442071
< 0.1%

post_code
Text

Missing 

Distinct29506
Distinct (%)63.9%
Missing3836
Missing (%)7.7%
Memory size781.2 KiB
2025-11-02T18:24:43.596582image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.107313058
Min length1

Characters and Unicode

Total characters328102
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20566 ?
Unique (%)44.5%

Sample

1st rowEH7 6RY
2nd rowEH14 5SX
3rd rowEH10 4BG
4th rowKY13 8RU
5th rowEH9 1EU
ValueCountFrequency (%)
eh61398
 
1.6%
eh101294
 
1.5%
eh71290
 
1.5%
eh31214
 
1.4%
eh41151
 
1.3%
eh12946
 
1.1%
eh9938
 
1.1%
eh11868
 
1.0%
eh8848
 
1.0%
eh16624
 
0.7%
Other values (9440)76540
87.9%
2025-11-02T18:24:44.110750image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40948
 
12.5%
127845
 
8.5%
E24316
 
7.4%
H22677
 
6.9%
215470
 
4.7%
412458
 
3.8%
312113
 
3.7%
511313
 
3.4%
611120
 
3.4%
010689
 
3.3%
Other values (63)139153
42.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)328102
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
40948
 
12.5%
127845
 
8.5%
E24316
 
7.4%
H22677
 
6.9%
215470
 
4.7%
412458
 
3.8%
312113
 
3.7%
511313
 
3.4%
611120
 
3.4%
010689
 
3.3%
Other values (63)139153
42.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)328102
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
40948
 
12.5%
127845
 
8.5%
E24316
 
7.4%
H22677
 
6.9%
215470
 
4.7%
412458
 
3.8%
312113
 
3.7%
511313
 
3.4%
611120
 
3.4%
010689
 
3.3%
Other values (63)139153
42.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)328102
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
40948
 
12.5%
127845
 
8.5%
E24316
 
7.4%
H22677
 
6.9%
215470
 
4.7%
412458
 
3.8%
312113
 
3.7%
511313
 
3.4%
611120
 
3.4%
010689
 
3.3%
Other values (63)139153
42.4%

post_code_prefix
Text

Missing 

Distinct9032
Distinct (%)19.6%
Missing3836
Missing (%)7.7%
Memory size781.2 KiB
2025-11-02T18:24:44.480644image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.330647258
Min length1

Characters and Unicode

Total characters246084
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3944 ?
Unique (%)8.5%

Sample

1st rowEH7 6
2nd rowEH14 5
3rd rowEH10 4
4th rowKY13 8
5th rowEH9 1
ValueCountFrequency (%)
55019
 
5.8%
15002
 
5.7%
64315
 
5.0%
44213
 
4.8%
24132
 
4.7%
94067
 
4.7%
84047
 
4.6%
33753
 
4.3%
73606
 
4.1%
02570
 
3.0%
Other values (5467)46381
53.2%
2025-11-02T18:24:44.958285image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40943
16.6%
127801
11.3%
E18882
 
7.7%
H17423
 
7.1%
215391
 
6.3%
412410
 
5.0%
312047
 
4.9%
511267
 
4.6%
611065
 
4.5%
010638
 
4.3%
Other values (60)68217
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)246084
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
40943
16.6%
127801
11.3%
E18882
 
7.7%
H17423
 
7.1%
215391
 
6.3%
412410
 
5.0%
312047
 
4.9%
511267
 
4.6%
611065
 
4.5%
010638
 
4.3%
Other values (60)68217
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)246084
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
40943
16.6%
127801
11.3%
E18882
 
7.7%
H17423
 
7.1%
215391
 
6.3%
412410
 
5.0%
312047
 
4.9%
511267
 
4.6%
611065
 
4.5%
010638
 
4.3%
Other values (60)68217
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)246084
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
40943
16.6%
127801
11.3%
E18882
 
7.7%
H17423
 
7.1%
215391
 
6.3%
412410
 
5.0%
312047
 
4.9%
511267
 
4.6%
611065
 
4.5%
010638
 
4.3%
Other values (60)68217
27.7%

country
Text

Missing 

Distinct82
Distinct (%)0.2%
Missing4609
Missing (%)9.2%
Memory size781.2 KiB
2025-11-02T18:24:45.173106image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length36
Median length14
Mean length13.54457932
Min length4

Characters and Unicode

Total characters614802
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)< 0.1%

Sample

1st rowUnited Kingdom
2nd rowUnited Kingdom
3rd rowUnited Kingdom
4th rowUnited Kingdom
5th rowUnited Kingdom
ValueCountFrequency (%)
united42476
48.2%
kingdom39946
45.3%
states2503
 
2.8%
australia484
 
0.5%
ireland425
 
0.5%
germany323
 
0.4%
canada217
 
0.2%
netherlands169
 
0.2%
france139
 
0.2%
switzerland108
 
0.1%
Other values (89)1311
 
1.5%
2025-11-02T18:24:45.489134image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n84408
13.7%
d83598
13.6%
i83532
13.6%
t48478
7.9%
e47027
7.6%
42710
6.9%
U42480
6.9%
m40459
6.6%
o40246
6.5%
g40173
6.5%
Other values (41)61691
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)614802
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n84408
13.7%
d83598
13.6%
i83532
13.6%
t48478
7.9%
e47027
7.6%
42710
6.9%
U42480
6.9%
m40459
6.6%
o40246
6.5%
g40173
6.5%
Other values (41)61691
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)614802
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n84408
13.7%
d83598
13.6%
i83532
13.6%
t48478
7.9%
e47027
7.6%
42710
6.9%
U42480
6.9%
m40459
6.6%
o40246
6.5%
g40173
6.5%
Other values (41)61691
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)614802
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n84408
13.7%
d83598
13.6%
i83532
13.6%
t48478
7.9%
e47027
7.6%
42710
6.9%
U42480
6.9%
m40459
6.6%
o40246
6.5%
g40173
6.5%
Other values (41)61691
10.0%
Distinct47310
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:45.788939image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters550000
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45067 ?
Unique (%)90.1%

Sample

1st row180:4199935
2nd row180:4239867
3rd row180:4359566
4th row180:4671469
5th row180:4500574
ValueCountFrequency (%)
180:40864619
 
< 0.1%
180:41365517
 
< 0.1%
180:40895196
 
< 0.1%
180:40606026
 
< 0.1%
180:40515436
 
< 0.1%
180:40588556
 
< 0.1%
180:41539965
 
< 0.1%
180:41233695
 
< 0.1%
180:40974785
 
< 0.1%
180:44615475
 
< 0.1%
Other values (47300)49940
99.9%
2025-11-02T18:24:46.224421image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
183586
15.2%
082639
15.0%
482270
15.0%
874641
13.6%
:50000
9.1%
332259
 
5.9%
532247
 
5.9%
231994
 
5.8%
630684
 
5.6%
725451
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)550000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
183586
15.2%
082639
15.0%
482270
15.0%
874641
13.6%
:50000
9.1%
332259
 
5.9%
532247
 
5.9%
231994
 
5.8%
630684
 
5.6%
725451
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)550000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
183586
15.2%
082639
15.0%
482270
15.0%
874641
13.6%
:50000
9.1%
332259
 
5.9%
532247
 
5.9%
231994
 
5.8%
630684
 
5.6%
725451
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)550000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
183586
15.2%
082639
15.0%
482270
15.0%
874641
13.6%
:50000
9.1%
332259
 
5.9%
532247
 
5.9%
231994
 
5.8%
630684
 
5.6%
725451
 
4.6%

no_of_tickets
Real number (ℝ)

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.14858
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:46.342967image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum60
Range59
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.439175253
Coefficient of variation (CV)0.6698262353
Kurtosis212.9039128
Mean2.14858
Median Absolute Deviation (MAD)1
Skewness8.282201072
Sum107429
Variance2.071225408
MonotonicityNot monotonic
2025-11-02T18:24:46.451066image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
224066
48.1%
114993
30.0%
34775
 
9.6%
44041
 
8.1%
5954
 
1.9%
6636
 
1.3%
7184
 
0.4%
8135
 
0.3%
1068
 
0.1%
943
 
0.1%
Other values (23)105
 
0.2%
ValueCountFrequency (%)
114993
30.0%
224066
48.1%
34775
 
9.6%
44041
 
8.1%
5954
 
1.9%
ValueCountFrequency (%)
602
< 0.1%
561
< 0.1%
431
< 0.1%
411
< 0.1%
401
< 0.1%
Distinct4199
Distinct (%)8.4%
Missing32
Missing (%)0.1%
Memory size781.2 KiB
2025-11-02T18:24:46.814304image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters799488
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)0.8%

Sample

1st row18/08/2023 21:40
2nd row06/08/2023 13:10
3rd row11/08/2023 15:20
4th row27/08/2023 21:10
5th row24/08/2023 13:25
ValueCountFrequency (%)
19/08/20232940
 
2.9%
12/08/20232755
 
2.8%
26/08/20232576
 
2.6%
18/08/20232484
 
2.5%
08/08/20232348
 
2.3%
25/08/20232281
 
2.3%
07/08/20232219
 
2.2%
17/08/20232135
 
2.1%
11/08/20232099
 
2.1%
20/08/20232038
 
2.0%
Other values (204)76061
76.1%
2025-11-02T18:24:47.290085image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0171592
21.5%
2145812
18.2%
/99936
12.5%
174651
9.3%
371569
9.0%
859229
 
7.4%
49968
 
6.2%
:49968
 
6.2%
529878
 
3.7%
414936
 
1.9%
Other values (3)31949
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)799488
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0171592
21.5%
2145812
18.2%
/99936
12.5%
174651
9.3%
371569
9.0%
859229
 
7.4%
49968
 
6.2%
:49968
 
6.2%
529878
 
3.7%
414936
 
1.9%
Other values (3)31949
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)799488
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0171592
21.5%
2145812
18.2%
/99936
12.5%
174651
9.3%
371569
9.0%
859229
 
7.4%
49968
 
6.2%
:49968
 
6.2%
529878
 
3.7%
414936
 
1.9%
Other values (3)31949
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)799488
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0171592
21.5%
2145812
18.2%
/99936
12.5%
174651
9.3%
371569
9.0%
859229
 
7.4%
49968
 
6.2%
:49968
 
6.2%
529878
 
3.7%
414936
 
1.9%
Other values (3)31949
 
4.0%

event
Text

Distinct2832
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:47.606160image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length120
Median length76
Mean length26.61108
Min length3

Characters and Unicode

Total characters1330554
Distinct characters110
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique318 ?
Unique (%)0.6%

Sample

1st rowJazz Emu: You Shouldn't Have
2nd rowNorthern Lights A Cappella's 10th B'day Bash: Top of the Bops
3rd rowThe Portable Dorothy Parker
4th rowBlues and Burlesque
5th rowAhir Shah: Ends
ValueCountFrequency (%)
the13598
 
6.0%
of5183
 
2.3%
a3555
 
1.6%
and3353
 
1.5%
in2345
 
1.0%
2253
 
1.0%
show2016
 
0.9%
to1566
 
0.7%
musical1468
 
0.7%
comedy1423
 
0.6%
Other values (5094)188231
83.7%
2025-11-02T18:24:48.071575image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175279
 
13.2%
e112215
 
8.4%
a79156
 
5.9%
o77446
 
5.8%
i69305
 
5.2%
n67493
 
5.1%
r66443
 
5.0%
t59286
 
4.5%
s52362
 
3.9%
l43882
 
3.3%
Other values (100)527687
39.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)1330554
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
175279
 
13.2%
e112215
 
8.4%
a79156
 
5.9%
o77446
 
5.8%
i69305
 
5.2%
n67493
 
5.1%
r66443
 
5.0%
t59286
 
4.5%
s52362
 
3.9%
l43882
 
3.3%
Other values (100)527687
39.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1330554
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
175279
 
13.2%
e112215
 
8.4%
a79156
 
5.9%
o77446
 
5.8%
i69305
 
5.2%
n67493
 
5.1%
r66443
 
5.0%
t59286
 
4.5%
s52362
 
3.9%
l43882
 
3.3%
Other values (100)527687
39.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1330554
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
175279
 
13.2%
e112215
 
8.4%
a79156
 
5.9%
o77446
 
5.8%
i69305
 
5.2%
n67493
 
5.1%
r66443
 
5.0%
t59286
 
4.5%
s52362
 
3.9%
l43882
 
3.3%
Other values (100)527687
39.7%
Distinct10
Distinct (%)< 0.1%
Missing163
Missing (%)0.3%
Memory size781.2 KiB
2025-11-02T18:24:48.222262image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length33
Median length19
Mean length10.03037904
Min length5

Characters and Unicode

Total characters499884
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowComedy
2nd rowMusic
3rd rowTheatre
4th rowCabaret and Variety
5th rowComedy
ValueCountFrequency (%)
comedy22978
29.3%
theatre14841
18.9%
and9238
11.8%
dance3712
 
4.7%
physical3712
 
4.7%
circus3712
 
4.7%
music3543
 
4.5%
opera3096
 
4.0%
musicals3096
 
4.0%
cabaret2430
 
3.1%
Other values (7)8010
 
10.2%
2025-11-02T18:24:48.477393image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e67225
13.4%
a44985
 
9.0%
d34847
 
7.0%
C31299
 
6.3%
r29140
 
5.8%
y29120
 
5.8%
28531
 
5.7%
o26113
 
5.2%
m22978
 
4.6%
h22963
 
4.6%
Other values (23)162683
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)499884
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e67225
13.4%
a44985
 
9.0%
d34847
 
7.0%
C31299
 
6.3%
r29140
 
5.8%
y29120
 
5.8%
28531
 
5.7%
o26113
 
5.2%
m22978
 
4.6%
h22963
 
4.6%
Other values (23)162683
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)499884
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e67225
13.4%
a44985
 
9.0%
d34847
 
7.0%
C31299
 
6.3%
r29140
 
5.8%
y29120
 
5.8%
28531
 
5.7%
o26113
 
5.2%
m22978
 
4.6%
h22963
 
4.6%
Other values (23)162683
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)499884
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e67225
13.4%
a44985
 
9.0%
d34847
 
7.0%
C31299
 
6.3%
r29140
 
5.8%
y29120
 
5.8%
28531
 
5.7%
o26113
 
5.2%
m22978
 
4.6%
h22963
 
4.6%
Other values (23)162683
32.5%

performance_reserved
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0048
Minimum0
Maximum1
Zeros49760
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:48.560747image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06911624658
Coefficient of variation (CV)14.39921804
Kurtosis203.3586118
Mean0.0048
Median Absolute Deviation (MAD)0
Skewness14.33005504
Sum240
Variance0.004777055541
MonotonicityNot monotonic
2025-11-02T18:24:48.635059image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
049760
99.5%
1240
 
0.5%
ValueCountFrequency (%)
049760
99.5%
1240
 
0.5%
ValueCountFrequency (%)
1240
 
0.5%
049760
99.5%

venue_server_id
Real number (ℝ)

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.29538
Minimum1
Maximum2814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:48.717811image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median33
Q361
95-th percentile911
Maximum2814
Range2813
Interquartile range (IQR)58

Descriptive statistics

Standard deviation307.8523001
Coefficient of variation (CV)2.418409058
Kurtosis22.18662998
Mean127.29538
Median Absolute Deviation (MAD)30
Skewness4.125703024
Sum6364769
Variance94773.03867
MonotonicityNot monotonic
2025-11-02T18:24:48.805563image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
3310153
20.3%
38732
17.5%
18143
16.3%
615203
10.4%
9113970
 
7.9%
143595
 
7.2%
1323022
 
6.0%
262102
 
4.2%
881994
 
4.0%
2311127
 
2.3%
Other values (9)1959
 
3.9%
ValueCountFrequency (%)
18143
16.3%
38732
17.5%
143595
 
7.2%
262102
 
4.2%
3310153
20.3%
ValueCountFrequency (%)
281419
 
< 0.1%
2542245
 
0.5%
183548
 
0.1%
913205
 
0.4%
9113970
7.9%

venue_id
Real number (ℝ)

Distinct168
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.80724
Minimum1
Maximum1357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:48.924957image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q319
95-th percentile909
Maximum1357
Range1356
Interquartile range (IQR)18

Descriptive statistics

Standard deviation295.2323045
Coefficient of variation (CV)2.527517168
Kurtosis7.236850825
Mean116.80724
Median Absolute Deviation (MAD)4
Skewness2.871617042
Sum5840362
Variance87162.11361
MonotonicityNot monotonic
2025-11-02T18:24:49.063638image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
117256
34.5%
173810
 
7.6%
23422
 
6.8%
162341
 
4.7%
51935
 
3.9%
41793
 
3.6%
241757
 
3.5%
31714
 
3.4%
61687
 
3.4%
191601
 
3.2%
Other values (158)12684
25.4%
ValueCountFrequency (%)
117256
34.5%
23422
 
6.8%
31714
 
3.4%
41793
 
3.6%
51935
 
3.9%
ValueCountFrequency (%)
13571
 
< 0.1%
13533
 
< 0.1%
1350106
0.2%
13477
 
< 0.1%
13444
 
< 0.1%

venue
Text

Distinct207
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:49.408833image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length49
Median length40
Mean length22.09166
Min length4

Characters and Unicode

Total characters1104583
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowPleasance Courtyard
2nd rowtheSpace @ Surgeons Hall
3rd rowtheSpace @ Surgeons Hall
4th rowThe Voodoo Rooms
5th rowMonkey Barrel Comedy
ValueCountFrequency (%)
pleasance10153
 
6.2%
the10049
 
6.1%
assembly8732
 
5.3%
8351
 
5.1%
square7972
 
4.9%
courtyard7339
 
4.5%
george5463
 
3.3%
underbelly4204
 
2.6%
comedy3904
 
2.4%
gilded3595
 
2.2%
Other values (354)94125
57.4%
2025-11-02T18:24:49.896568image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e136116
 
12.3%
115680
 
10.5%
a78313
 
7.1%
r66948
 
6.1%
l64297
 
5.8%
o59263
 
5.4%
s58855
 
5.3%
t45971
 
4.2%
n43058
 
3.9%
u37382
 
3.4%
Other values (60)398700
36.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1104583
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e136116
 
12.3%
115680
 
10.5%
a78313
 
7.1%
r66948
 
6.1%
l64297
 
5.8%
o59263
 
5.4%
s58855
 
5.3%
t45971
 
4.2%
n43058
 
3.9%
u37382
 
3.4%
Other values (60)398700
36.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1104583
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e136116
 
12.3%
115680
 
10.5%
a78313
 
7.1%
r66948
 
6.1%
l64297
 
5.8%
o59263
 
5.4%
s58855
 
5.3%
t45971
 
4.2%
n43058
 
3.9%
u37382
 
3.4%
Other values (60)398700
36.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1104583
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e136116
 
12.3%
115680
 
10.5%
a78313
 
7.1%
r66948
 
6.1%
l64297
 
5.8%
o59263
 
5.4%
s58855
 
5.3%
t45971
 
4.2%
n43058
 
3.9%
u37382
 
3.4%
Other values (60)398700
36.1%

subvenue_id
Real number (ℝ)

Distinct265
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean210.67234
Minimum1
Maximum2068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:50.026717image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median20
Q363
95-th percentile1600
Maximum2068
Range2067
Interquartile range (IQR)56

Descriptive statistics

Standard deviation481.1061719
Coefficient of variation (CV)2.283670328
Kurtosis5.685901756
Mean210.67234
Median Absolute Deviation (MAD)18
Skewness2.637698541
Sum10533617
Variance231463.1486
MonotonicityNot monotonic
2025-11-02T18:24:50.165596image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13463
 
6.9%
52299
 
4.6%
142058
 
4.1%
41929
 
3.9%
31842
 
3.7%
21475
 
2.9%
441399
 
2.8%
111357
 
2.7%
61352
 
2.7%
161139
 
2.3%
Other values (255)31687
63.4%
ValueCountFrequency (%)
13463
6.9%
21475
2.9%
31842
3.7%
41929
3.9%
52299
4.6%
ValueCountFrequency (%)
20681
< 0.1%
20672
< 0.1%
20661
< 0.1%
20651
< 0.1%
20601
< 0.1%
Distinct350
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:50.489352image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length54
Median length33
Mean length11.79734
Min length3

Characters and Unicode

Total characters589867
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowPleasance Two
2nd rowGrand Theatre
3rd rowGrand Theatre
4th rowThe Ballroom
5th rowMonkey Barrel 3
ValueCountFrequency (%)
theatre6274
 
6.2%
the6101
 
6.1%
hall5119
 
5.1%
room3800
 
3.8%
studio2865
 
2.8%
grand2764
 
2.7%
main2500
 
2.5%
12185
 
2.2%
monkey2135
 
2.1%
barrel2135
 
2.1%
Other values (385)64942
64.4%
2025-11-02T18:24:50.932815image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e68010
 
11.5%
52980
 
9.0%
a47889
 
8.1%
r35625
 
6.0%
n34243
 
5.8%
o34090
 
5.8%
t33470
 
5.7%
l28853
 
4.9%
i27262
 
4.6%
h18023
 
3.1%
Other values (58)209422
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)589867
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e68010
 
11.5%
52980
 
9.0%
a47889
 
8.1%
r35625
 
6.0%
n34243
 
5.8%
o34090
 
5.8%
t33470
 
5.7%
l28853
 
4.9%
i27262
 
4.6%
h18023
 
3.1%
Other values (58)209422
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)589867
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e68010
 
11.5%
52980
 
9.0%
a47889
 
8.1%
r35625
 
6.0%
n34243
 
5.8%
o34090
 
5.8%
t33470
 
5.7%
l28853
 
4.9%
i27262
 
4.6%
h18023
 
3.1%
Other values (58)209422
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)589867
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e68010
 
11.5%
52980
 
9.0%
a47889
 
8.1%
r35625
 
6.0%
n34243
 
5.8%
o34090
 
5.8%
t33470
 
5.7%
l28853
 
4.9%
i27262
 
4.6%
h18023
 
3.1%
Other values (58)209422
35.5%
Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size781.2 KiB
2025-11-02T18:24:51.061448image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Length

Max length38
Median length3
Mean length3.24272
Min length3

Characters and Unicode

Total characters162136
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowWeb
2nd rowWeb
3rd rowWeb
4th rowWeb
5th rowWeb
ValueCountFrequency (%)
web48114
95.0%
counters1038
 
2.1%
phones646
 
1.3%
207
 
0.4%
customer201
 
0.4%
services201
 
0.4%
default191
 
0.4%
fringe10
 
< 0.1%
central5
 
< 0.1%
industry4
 
< 0.1%
Other values (9)17
 
< 0.1%
2025-11-02T18:24:51.284126image/svg+xmlMatplotlib v3.10.7, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e50616
31.2%
W48114
29.7%
b48114
29.7%
s2098
 
1.3%
o1890
 
1.2%
n1711
 
1.1%
r1465
 
0.9%
t1446
 
0.9%
u1435
 
0.9%
C1245
 
0.8%
Other values (22)4002
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)162136
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e50616
31.2%
W48114
29.7%
b48114
29.7%
s2098
 
1.3%
o1890
 
1.2%
n1711
 
1.1%
r1465
 
0.9%
t1446
 
0.9%
u1435
 
0.9%
C1245
 
0.8%
Other values (22)4002
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)162136
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e50616
31.2%
W48114
29.7%
b48114
29.7%
s2098
 
1.3%
o1890
 
1.2%
n1711
 
1.1%
r1465
 
0.9%
t1446
 
0.9%
u1435
 
0.9%
C1245
 
0.8%
Other values (22)4002
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)162136
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e50616
31.2%
W48114
29.7%
b48114
29.7%
s2098
 
1.3%
o1890
 
1.2%
n1711
 
1.1%
r1465
 
0.9%
t1446
 
0.9%
u1435
 
0.9%
C1245
 
0.8%
Other values (22)4002
 
2.5%